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Numerical simulation of intelligent compaction for subgrade construction

路基智能压实技术的数值仿真

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Abstract

During the compaction of a road subgrade, the mechanical parameters of the soil mass change in real time, but current research assumes that these parameters remain unchanged. In order to address this discrepancy, this paper establishes a relationship between the degree of compaction K and strain ε. The relationship between the compaction degree K and the shear strength of soil (cohesion c and frictional angle ϕ) was clearly established through indoor experiments. The subroutine UMAT in ABAQUS finite element numerical software was developed to realize an accurate calculation of the subgrade soil compaction quality. This value was compared and analyzed against the assumed compaction value of the model, thereby verifying the accuracy of the intelligent compaction calculation results for subgrade soil. On this basis, orthogonal tests of the influential factors (frequency, amplitude, and quality) for the degree of compaction and sensitivity analysis were carried out. Finally, the ‘acceleration intelligent compaction value’, which is based on the acceleration signal, is proposed for a compaction meter value that indicates poor accuracy. The research results can provide guidance and basis for further research into the accurate control of compaction quality for roadbeds and pavements.

摘要

k]在路基压实过程中,土体的力学参数是实时变化的,但在目前的研究中,假设这些参数保 持不变。为了解决这一矛盾,本文建立了压实度K 和应变ε 之间的关系,并通过室内实验得到压实度 K 与土体的抗剪强度(黏聚力c 和摩擦角ϕ)之间的关系。为了实现路基压实质量的精确计算,对 ABAQUS 有限元数值软件进行了二次开发。将数值仿真的结果与模型假定的压实值进行对比分析,验 证了路基土智能压实计算结果的准确性。在此基础上,对影响压实度的因素进行了正交试验和敏感度 分析。最后,针对精度较差的压实质量评价指标,提出了更为精确的压实质量评价指标。研究结果可 为进一步研究路基路面压实质量的准确控制提供指导和依据。

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References

  1. XU Qin-wu, CHANG G K. Evaluation of intelligent compaction for asphalt materials [J]. Automation in Construction, 2013, 30: 104–12. DOI: https://doi.org/10.1016/j.autcon.2012.11.015.

    Article  Google Scholar 

  2. XU Qin-wu, CHANG G. K, GALLIVAN V L. Development of a systematic method for intelligent compaction data analysis and management [J]. Construction and Building Materials, 2012, 37: 470–480. DOI: https://doi.org/10.1016/j.conbuildmat.2012.08.001.

    Article  Google Scholar 

  3. VENNAPUSA P K R, WHITE D J, SCHRAM S. Roller-integrated compaction monitoring for hot-mix asphalt overlay construction [J]. Journal of Transportation Engineering, 2013, 139: 1164–1173. DOI: https://doi.org/10.1061/(ASCE)TE.1943-5436.0000602.

    Article  Google Scholar 

  4. Intelligent Compaction Website. What is intelligent compaction in learn ICT in 2011: America [EB/OL]. http://www.intelligentcompaction.com.

  5. ZHAO Xiao-ping. Study on intelligent compaction control technology of subgrade [D]. Xi’an: Changan University, 2016. (in Chinese)

    Google Scholar 

  6. MOONEY M A, GORMAN P B, GONZALEZ J N. Vibration based health monitoring during earthwork construction [J]. Journal of Structural Health Monitoring, 2005, 2(4): 137–152.

    Article  Google Scholar 

  7. MINCHIN R E, THOMAS H R. Validation of vibration-based onboard asphalt density measuring system [J]. Journal of Construction Engineering and Management, 2003, 129: 1–7. DOI: https://doi.org/10.1061/(ASCE)0733-9364(2003)129:1(1).

    Article  Google Scholar 

  8. CAI Hu-bo, KUCZEK T, DUNSTON P S, LI Shuai. Intelligent compaction data to in situ soil compaction quality measurements [J]. Journal of Construction Engineering and Management, 2017, 143(8): 04017038. DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001333.

    Article  Google Scholar 

  9. WHITE D J, THOMPSON M J. Relationships between in situ and roller integrated compaction measurements for granular soils [J]. Journal of Geotechnical and Geoenvironmental Engineering, 2008, 134: 1763–1770. DOI: https://doi.org/10.1061/(ASCE)1090-0241(2008)134:12(1763).

    Article  Google Scholar 

  10. LING Jian-ming, LIN Sheng, QIAN Jin-song. Continuous compaction control technology for granite residual subgrade compaction [J]. Journal of Materials in Civil Engineering, 2018, 30(12): 04018316. DOI: https://doi.org/10.1061/(ASCE)MT.1943-5533.0002522.

    Article  Google Scholar 

  11. HU Wei, SHU Xiang, JIA Xiao-yang. Geostatistical analysis of intelligent compaction measurements for asphalt pavement compaction [J]. Automation in Construction, 2018, 89: 162–169. DOI: https://doi.org/10.1016/j.autcon.2018.01.012.

    Article  Google Scholar 

  12. THOMPSON M J, WHITE D J. Field calibration and spatial analysis of compaction-monitoring technology measurements [J]. Transportation Research Record Journal of the Transportation Research Board, 2007, 2004: 69–79. DOI: https://doi.org/10.3141/2004-08.

    Article  Google Scholar 

  13. WHITE D J, VENNAPUSA P K R, GIESELMAN H H. Field assessment and specification review for roller-integrated compaction monitoring technologies [J]. Advances in Civil Engineering, 2011(2): 1–15. DOI: https://doi.org/10.1155/2011/783836.

  14. ZHANG Yao, MA Tao, LING Meng, ZHANG De-yu, HUANG Xiao-ming. Predicting dynamic shear modulus of asphalt mastics using discretized- element simulation and reinforcement mechanisms [J]. Journal of Materials in Civil, 2019, 31(8). DOI: https://doi.org/10.1061/(ASCE)MT.1943-5533.0002831.

  15. ZHANG Yao, MA Tao, DING Xun-hao, HUANG Xiao-ming, XU Guang-ji. Impacts of Air-void structures on the rutting tests of asphalt concrete based on discretized emulation [J]. Construction and Building Materials, 2018, 166: 334–344. DOI: https://doi.org/10.1016/j.conbuildmat.2018.01.141.

    Article  Google Scholar 

  16. CHEN Tian, LUAN Ying-cheng, MA Tao, ZHU Jun-qing, HUANG Xiao-ming, MA Shi-jie. Mechanical and microstructural characteristics of different interfaces in cold recycled mixture containing cement and asphalt emulsion [J]. Journal of Cleaner Production, 2020, 258. DOI: https://doi.org/10.1016/j.jclepro.2020.120674.

  17. MA Tao, WANG Hao, ZHANG De-yu, ZHANG Yao. Heterogeneity effect of mechanical property on creep behavior of asphalt mixture based on micromechanical modeling and virtual creep test [J]. Mechanics of Materials, 2017, 104: 49–59. DOI: https://doi.org/10.1016/j.mechmat.2016.10.003.

    Article  Google Scholar 

  18. TANG Fan-long, MA Tao, ZHANG Jun-hui. Integrating three-dimensional road design and pavement structure analysis based on BIM [J]. Automation in Construction, 2020, 113: 103152. DOI: https://doi.org/10.1016/j.autcon.2020.103152.

    Article  Google Scholar 

  19. ZHANG Yao, MA Tao, LING Meng, HUANG Xiao-ming. Mechanistic sieve-size classification of aggregate gradation by characterizing load-carrying capacity of inner structures [J]. Journal of Engineering Mechanics, 2019, 145(9). DOI: https://doi.org/10.1061/(ASCE)EM.1943-7889.0001640.

  20. JTG E40-2007: Test methods of soils for highway engineering, China [S]. (in Chinese)

  21. MA Tao, ZHANG De-yu, ZHANG Yao, WANG Si-qi. Simulation of wheel tracking test for asphalt mixture using discrete element modelling [J]. Road Materials and Pavement Design, 2018, 19: 367–384. DOI: https://doi.org/10.1080/14680629.2016.1261725.

    Article  Google Scholar 

  22. DING Xun-hao, MA Tao, HUANG Xiao-ming. Discrete-element contour-filling modeling method for micro-and micromechanical analysis of aggregate skeleton of asphalt mixture [J]. Journal of Transportation Engineering, Part B: Pavements, 2019, 145(1): 04018056. DOI: https://doi.org/10.1061/JPEODX.0000083.

    Article  Google Scholar 

  23. DING Xun-hao, CHEN Lu-chuan, MA Tao, MA Hai-xia, GU Lin-hao, CHEN Tian, MA Yuan. Laboratory investigation of the recycled asphalt concrete with stable crumb rubber asphalt binder [J]. Construction and Building Materials, 2019, 203: 552–557. DOI: https://doi.org/10.1016/j.conbuildmat.2019.01.114.

    Article  Google Scholar 

  24. TANG Fan-long, MA Tao, GUAN Yong-sheng, ZHANG Zhi-xiang. Parametric modeling and structure verification of asphalt pavement based on BIM-ABAQUS [J]. Automation in Construction, 2020, 111: 103066. DOI: https://doi.org/10.1016/j.autcon.2019.103066.

    Article  Google Scholar 

  25. DING Xun-hao, MA Tao, GU Lin-hao, ZHANG De-yu, HUANG Xiao-ming. Discrete element methods for characterizing the elastic behavior of the granular particles [J]. Journal of Testing and Evaluation, 2020, 48(3): 20190178. DOI: https://doi.org/10.1520/JTE20190178.

    Article  Google Scholar 

  26. ZHANG Wei-guang, AKBER M A, HOU Shu-guang, BIAN Jiang, ZHANG Dong, LE Qi-qi. Detection of dynamic modulus and crack properties of asphalt pavement using a non-destructive ultrasonic wave method [J]. Apply Science, 2019, 9(15): 2946. DOI: https://doi.org/10.3390/app9152946.

    Article  Google Scholar 

  27. XIA Wei-yi, DU Yan-jun, LI Fa-sheng, LI Chun-ping, YAN Xiu-lan, ARUL A, WANG Fei, SONG De-jun. In-situ solidification/stabilization of heavy metals contaminated site soil using a dry jet mixing method and new hydroxyapatite based binder [J]. Journal of Hazardous Materials, 2019, 369: 353–361. DOI: https://doi.org/10.1016/j.jhazmat.2019.02.031.

    Article  Google Scholar 

  28. XIA Wei-yi, FENG Ya-song, JIN Fei, ZHANG Li-ming, DU Yan-jun. Stabilization and solidification of a heavy metal contaminated site soil using a hydroxyapatite based binder [J]. Construction and Building Materials, 2017, 156: 199–207. DOI: https://doi.org/10.1016/j.jhazmat.2019.02.031.

    Article  Google Scholar 

  29. WU Hao-liang, JIN Fei, BO Yun-lin, DU Yan-jun, ZHENG Jun-xing. Leaching and microstructural properties of lead contaminated kaolin stabilized by GGBS-MgO in semi-dynamic leaching tests [J]. Construction and Building Materials, 2018, 172: 626–634. DOI: https://doi.org/10.1016/j.conbuildmat.2018.03.164.

    Article  Google Scholar 

  30. JIANG Ning-jun, DU Yan-jun, LIU Kai. Durability of lightweight alkali-activated ground granulated blast furnace slag (GGBS) stabilized clayey soils subjected to sulfate attack [J]. Applied Clay Science, 2018, 161: 70–75. DOI: https://doi.org/10.1016/j.clay.2018.04.014.

    Article  Google Scholar 

  31. LIU Guo-qiang, YANG Tao, LI Jing, JIA Yan-shun, ZHAO Yong-li, ZHANG Jun-peng. Effects of aging on theological properties of asphalt materials and asphalt-filler interaction ability [J]. Construction and Building Materials, 2018, 168: 501–511. DOI: https://doi.org/10.1016/j.conbuildmat.2018.02.171.

    Article  Google Scholar 

  32. CHEN An-qi, LIU Guo-qiang, ZHAO Yong-li, LI Jing, PAN Yuan-yuan, ZHOU Jian. Research on the aging and rejuvenation mechanisms of asphalt using atomic force microscopy [J]. Construction and Building Materials, 2018, 167: 177–184. DOI: https://doi.org/10.1016/j.conbuildmat.2018.02.008.

    Article  Google Scholar 

  33. MA Tao, WANG Hao, HE Liang, ZHAO Yong-li, HUANG Xiao-ming, CHEN Jun. Property characterization of asphalt and mixtures modified by different crumb rubbers [J]. Journal of Materials in Civil Engineering, 2017, 29(7): 1–10. DOI: https://doi.org/10.1061/(ASCE)MT.1943-5533.0001890.

    Article  Google Scholar 

  34. MA Tao, ZHANG De-yu, ZHANG Yao, WANG Si-qi, HUANG Xiao-ming. Simulation of wheel tracking test for asphalt mixture using discrete element modelling [J]. Road Materials and Pavement Design, 2018, 19(2): 367–384. DOI: https://doi.org/10.1080/14680629.2016.1261725.

    Article  Google Scholar 

  35. ZHANG Jun-hui, DING Le, LI Feng, PENG Jun-hui. Recycled aggregates from construction and demolition wastes as alternative filling materials for highway subgrades in China [J]. Journal of Cleaner Production, 2020, 255: 120223. DOI: https://doi.org/10.1016/j.jclepro.2020.120223.

    Article  Google Scholar 

  36. ZHANG Jun-hui, PENG Jun-hui, LIU Wei-zheng, LU Wei-hua. Predicting resilient modulus of fine-grained subgrade soils considering relative compaction and matric suction [J]. Road Materials and Pavement Design, 2019, 1: 1–13. DOI: https://doi.org/10.1080/14680629.2019.1651756.

    Google Scholar 

  37. ZENG Ling, XIAO Liu-yi, ZHANG Jun-hui, PENG Jun-hui. The role of nanotechnology in subgrade and pavement engineering: A review [J]. Journal of Nanoscience and Nanotechnology, 2020, 255120223. DOI: https://doi.org/10.1016/j.jclepro.2020.120223.

  38. YU Hua-nan, SHEN Shi-hui, QIAN Guo-ping, GONG Xiang-bing. Packing theory and volumetrics-based aggregate gradation design method [J]. Journal of Materials in Civil Engineering, 2020, 32(6): 04020110. DOI: https://doi.org/10.1061/(asce)mt.1943-5533.0003192.

    Article  Google Scholar 

  39. YU Hua-nan, HE Zhi-yu, QIAN Guo-ping, GONG Xiang-bing, QU Xiang. Research on the anti-icing properties of silicone modified polyurea coatings (SMPC) for asphalt pavement [J]. Construction and Building Materials, 2020, 242, 117793. DOI: https://doi.org/10.1016/j.conbuildmat.2019.117793.

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Transportation, Southeast University, Nanjing, 210096, China

    Yuan Ma  (马源), Ying-cheng Luan  (栾英成) & Wei-guang Zhang  (张伟光)

  2. National Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science & Technology, Changsha, 410114, China

    Yu-qing Zhang  (张裕卿)

  3. Aston Institute of Materials Research, Engineering Systems & Management Group, Aston University, Birmingham, B4 7ET, UK

    Yu-qing Zhang  (张裕卿)

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  1. Yuan Ma  (马源)
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  2. Ying-cheng Luan  (栾英成)
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  3. Wei-guang Zhang  (张伟光)
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Contributions

The authors confirm contributions to the paper as follows. Study conception and design: ZHANG Wei-guang and ZHANG Yu-qing; data collection: MA Yuan; analysis and interpretation of results: MA Yuan and LUAN Ying-cheng; draft manuscript preparation: MA Yuan, LUAN Ying-cheng; draft revision: ZHANG Wei-guang, ZHANG Hui. All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Wei-guang Zhang  (张伟光).

Additional information

Foundation item: Project(51878164) supported by the National Natural Science Foundation of China; Projects(BK20161421, BK20140109) supported by the Natural Science Foundation of Jiangsu Province, China; Project(141076) supported by the Huoyingdong Foundation of the Ministry of Education of China; Project(BZ2017011) supported by the Science and Technology Support Project of Jiangsu Province, China; Project(2242015R30027) supported by the Fundamental Research Funds for the Central Universities, China; Project(grant number KFJ170106) supported by the Changsha University of Science & Technology via Open Fund of National Engineering Laboratory of Highway Maintenance Technology, China; Project(2018B51) supported by the Science and Technology Support Project of Qilu Transportation Development Group, China

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Ma, Y., Luan, Yc., Zhang, Wg. et al. Numerical simulation of intelligent compaction for subgrade construction. J. Cent. South Univ. 27, 2173–2184 (2020). https://doi.org/10.1007/s11771-020-4439-2

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  • DOI: https://doi.org/10.1007/s11771-020-4439-2

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